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PROCRASTINATION, Present-Biased Preferences and Financial Behaviors

PROCRASTINATION, Present-Biased Preferences and Financial Behaviors. Jeffrey R. Brown University of Illinois and NBER Alessandro Previtero Ivey Business School, Western University. Present-Bias and Procrastination. Economists model procrastination as the result of present-biased preferences

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PROCRASTINATION, Present-Biased Preferences and Financial Behaviors

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  1. PROCRASTINATION, Present-Biased Preferences and Financial Behaviors Jeffrey R. Brown University of Illinois and NBER Alessandro Previtero Ivey Business School, Western University

  2. Present-Bias and Procrastination • Economists model procrastination as the result of present-biased preferences • Near term costs + distant consequences  delay • Theory: Akerlof (Ely Lecture, 1991); Laibson (1997); O’Donoghue & Rabin (1999a, 1999b, 2001); Fudenberg & Levine (2006, 2012) • If true, then this this has implications for retirement planning behaviors, policy and plan design  Direct empirical evidence on relevance of present-biased preferences and procrastination is very limited

  3. Highly Relevant to Retirement • DC system provides more autonomy, and also more room for mistakes (Benartzi and Thaler, 2007) • We still do not fully understand why there is such a large dispersion of wealth at retirement (Poterba, Venti, Wise, 2013) • Intuitively, procrastination is a likely culprit, especially because it is more likely “the further away an event is temporally” (Steel, 2007) • Procrastination has been suggested as a reason default options may exert such a power influence on behavior (Beshears et al 2009)  If we can establish that present-biased preferences and procrastination negatively affect retirement security, we can better guide policy and plan design to improve outcomes

  4. Measuring Procrastination • We empirically define “procrastinators” as people who wait until the last day of open enrollment period to make their health care plan election • The advantages of our measure of procrastination: • Actual and consequential behavior (Levitt and List, 2008) • Distinct decision from outcomes being studied (Kuchler, 2014) • Can be implemented in multiple data sets • Four measures • Procr_max: ever procrastinate in any year of data • Procr_mean: fraction of elections made in which procrastinated • Procr_first: whether procrastinated the first time a choice was made • Procr_ last: whether procrastinated the last time a choice was made

  5. Five Hypotheses to Test if Procrastination is Driven by Present-Biased Preferences Present-biased preferences will jointly predict that: • Procrastinators are less likely to participate in supplemental savings plans • Procrastinators who do save will take longer to sign up • Procrastinators will contribute less (conditional on participating at all) • Procrastinators will be more likely to stick with the default portfolio investment • Procrastinators will be less likely to annuitize

  6. Three Data Sets • 2,678 new employees joining U of I system during c.y. 2010 • Binary decision of whether to contribute to 403(b) or 457 • Over 100,000 participants in 27 401(k) plans • Days to join 401(k) • Contribution rates • Share of portfolio invested in QDIA (lifecycle, target date, balanced) • Over 27,000 employees ages 55+ who retire from DB plan • Annuity vs. lump-sum • In all three cases, we have information on exact date that health care plan was selected

  7. Table 2 Procrastinators 2.4% Points Less Likely to Sign Up for Supplemental Plan Note that although some covariates are significant, they have no effect on procrastination coefficient

  8. Table 3 Panel A Procrastinators Take 44-72 Days Longer to Join 401(k) Regressions are right censored at 5 years after hire Regressions also control for female (+), hiring age (-), plan and year controls

  9. Procrastinators Contribute 0.1-0.2% of PayLess (When Not Defaulted) Further refinements to methodology for identifying defaults underway – “hot off the press” results suggests that procrastinators who are auto-enrolled at firm with low default saving rate may also have lower contribution rate than non-procrastinators Table 4B

  10. Procrastinators Invest 3-5% More in QDIAs(Lifecycle, Target Date or Balanced) Regressions also control for female (+), hiring age (-), plan and year controls Table 5A

  11. Procrastinators 3-4% Pts More Likely to Have 100% Allocation to QDIA Post-PPA Regressions also control for female (+), hiring age (0), plan and year controls Table 5B

  12. Procrastinators 4-5% Pts Less Likely to Annuitize DB Regressions also control for female (+), hiring age (-), Value of DB (+), tenure (-), 6 month Interest rate (0), past 12m S&P (-), plan and year controls Table 6

  13. Evidence of Present-Biased Preferences • Optimal delayers (those who have multiple interactions, including final one on last day) behave opposite of procrastinators (i.e., save more, less likely to choose default, etc.) • Only present-biased preferences can explain: • Low saving rate • Lower probability of annuitizing • When lump-sum made more salient (cash balance plans), the negative effect on annuitization is even stronger

  14. And in a Separate Study … • RRC-Funded project by Brown, Farrell & Weisbenner surveys Illinois SURS participants • Those who wait until “final reminder” to return our survey are substantially more likely to be defaulted into lifetime DB plan • Current project is experimenting to see if reminders closer to default date reduce the probability of defaults – stay tuned!

  15. Summary of Findings • Procrastinators: • Are less likely to participate in supplemental savings plans • Take longer to sign up when they do participate • Contribute less • Are more likely to stick with the default investment option after passage of PPA 2006 • Are more likely to allocate 100% of their portfolio to the default investment option after passage of PPA 2006 • Are less likely to annuitize their DB at retirement • And even less likely to annuitize their cash balance plan • Only present-biased preferences can jointly explain all of these results

  16. Policy Relevance • Sheds light on a potentially important pathway through which default options exert influence • Provides guidance as to type of interventions that may be needed to increase active choice • Making choices more salient today; forced deadlines • Much more research is needed here! • Current policy discussion around retirement income need to account for present-biased preferences

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